Relationships Between Retinal Axonal and Neuronal Measures and Global Central Nervous System Pathology in Multiple Sclerosis ONLINE FIRST

Figure 1. Eye of a healthy control subject. A, Fundus photograph from a healthy control subject. B, A 3-dimensional macular volume cube generated by Cirrus HD-OCT from the macular region denoted by the red box in panel A from the same healthy control subject. Note the individual layers of the retina are readily discernible, except for the ganglion cell layer (GCL) and inner plexiform layer (IPL), which are difficult to distinguish. During the segmentation process (performed in 3-dimension), the segmentation software identifies the outer boundaries of the macular retinal nerve fiber layer (RNFL), IPL, and outer plexiform layer (OPL), as well as the inner boundary of the retinal pigment epithelium (RPE), which is identified by the conventional Cirrus HD-OCT algorithm. The identification of these boundaries facilitates OCT segmentation, enabling determination of the thicknesses of the macular RNFL, GCL + IPL, the inner nuclear layer (INL) + OPL, and the outer nuclear layer (ONL) including the inner and outer photoreceptor segments. C, Illustration of the cellular composition of the retinal layers depicted in panel B. ELM indicates external limiting membrane; ILM, inner limiting membrane; IPS, inner photoreceptor segments; OPS, outer photoreceptor segments; PR, photoreceptors.

Figure 2. Adjusted variables plots. A, An adjusted variables plot of ganglion cell layer + inner plexiform layer (GCL + IPL) thickness and intracranial volume (ICV) in multiple sclerosis (MS), adjusted for age, sex, and disease duration. The solid line graphically illustrates the independent relationship between GCL + IPL thickness and ICV in MS. As ICV increases, GCL + IPL thickness similarly increases, consistent with the detection of significant associations between GCL + IPL thickness and ICV in MS (P = .008). B, An adjusted variables plot of GCL + IPL thickness and ICV in healthy control subjects, adjusted for age and sex. The solid line graphically illustrates the independent relationship between GCL + IPL thickness and ICV in healthy control subjects. As ICV increases, GCL + IPL thickness similarly increases, consistent with the detection of significant associations between GCL + IPL thickness and ICV in healthy control subjects (P = .04). C, An adjusted variables plot of inner nuclear layer (INL) thickness and normal-appearing white matter (NAWM) volume in MS, adjusted for age, sex, disease duration, and ICV. The solid line graphically illustrates the independent relationship between INL thickness and NAWM volume in MS. As INL thickness increases, NAWM volume decreases, consistent with the detection of significant inverse associations between INL thickness and NAWM volume in MS (P = .01). Moreover, although not depicted in this figure, greater INL thickness was also associated with greater fluid-attenuated inversion recovery lesion volume in relapsing-remitting MS (RRMS) (P = .02). Because INL pathology in MS is thought to result from primary retinal mechanisms of pathology, rather than being related to optic neuropathy, these findings indicate the possibility that the potential mechanism underlying the proposed occurrence of primary retinal pathology affecting the INL in MS may be inflammatory, such as related to retinal periphlebitis. D, An adjusted variables plot of peripapillary retinal nerve fiber layer (pRNFL) thickness and cortical gray matter (GM) volume in RRMS, adjusted for age, sex, disease duration, and ICV. The solid line graphically illustrates the independent relationship between RNFL thickness and cortical GM volume in RRMS. As RNFL thickness decreases, cortical GM volume similarly decreases, consistent with the detection of significant associations between RNFL thickness and cortical GM volume in RRMS (P = .01). * Residual values from multivariate regression models.